We evaluated whether gamified training improves compensation for population-coding distortions in sight recovery by testing transfer of learning between a dichoptic object recognition task and a filtered version of Fruit Ninja, finding no significant transfer and suggesting limited generalizability of gamification-based rehabilitation.
Using an immersive VR system, we systematically evaluated two behavioral tasks under four raster patterns (horizontal, vertical, checkerboard, and random) and found checkerboard raster to be the most effective.
We present insights from 16 semi-structured interviews with individuals who are either legally or completely blind, highlighting both the current use and potential future applications of technologies for home-based iADLs.
Our interview study found a significant gap between researcher expectations and implantee experiences with visual prostheses, underscoring the importance of focusing future research on usability and real-world application.
We retrospectively analyzed phosphene shape data collected form three Argus II patients to investigate which neuroanatomical and stimulus parameters predict paired-phosphene appearance and whether phospehenes add up linearly.
We present explainable artificial intelligence (XAI) models fit on a large longitudinal dataset that can predict perceptual thresholds on individual Argus II electrodes over time.
We present a biophysically detailed *in silico* model of retinal degeneration that simulates the network-level response to both light and electrical stimulation as a function of disease progression.
We present a systematic literature review of 227 publications from 106 different venues assessing the potential of XR technology to further visual accessibility.